Really getting burnt out on compass laying/circle casting tech. I'm sure different things work for different people, but it's just not working for me as well as other techniques of power raising and spirit calling. I've been trying different ways of tapping the power that already exists in the land (as opposed to calling it from Elsewhere), as well as using a bullroarer made from scraps I got from a woodworking class way back when.
I guess this should be a lesson to me that what is formulaic in a lot of trad craft books is not always best for an individual.
The thing that pisses me off the most with my ADHD Approved Executive Dysfunction™ is the fact I excel at Methodology and Planning. Literally, I was the Methodology teacher's favorite back in college. I just absolutely SUCK at actually following my plans and methodology. Yes, even when I precisely make those plans and methodologies to cater to my needs and strengths and weaknesses because the biggest issue is STARTING, ALWAYS!
how to catch a compound lying about where it came from
a methodology post for @kaiasky, who asked how you look at a database entry and decide it doesn’t belong
(i post programmatically, so the two images above appear before the text rather than inline. the first shows what a “natural” molecule’s architecture looks like, the second shows “synthetic.” they’re meant to accompany section i.)
a few days ago I posted about finding four synthetic imposters hiding in NPASS, a database of natural products. @kaiasky asked a wonderful question: how do you actually decide a compound is mislabeled?
the short answer is that natural products have an accent.
i. the accent
every molecule carries the fingerprints of whatever built it. enzymes build molecules the way a particular carpenter builds furniture — there are shapes they reach for, joints they prefer, materials they keep in stock.
biological enzymes work with a limited pantry. they like oxygen and nitrogen. they build rings by fusing them together in flowing, asymmetric patterns. they attach sugars. they leave hydroxyl groups (-OH) everywhere, like a trail of breadcrumbs. the resulting molecules tend to look organic in the oldest sense of the word: curved, irregular, decorated.
pharmaceutical chemists work from a different pantry. they reach for halogens (chlorine, fluorine, bromine) because these are excellent for tuning how a drug binds to its target but are rarely used by biology. they build symmetric scaffolds because symmetry is easier to synthesize at scale. they use linker groups like hydrazones or sulfonamides that connect modular pieces together like lego bricks.
when a synthetic compound wanders into a natural products database, it’s like hearing someone speak with a completely different accent at a regional dialect convention. it doesn’t prove they’re from somewhere else (accents can surprise you) but it tells you to ask follow-up questions.
ii. the interrogation
once a compound sounds suspicious, you run it through a series of checkpoints. each one is a different kind of question, and a compound needs to fail multiple checks before you call it an imposter. one red flag is a curiosity. three red flags is a case.
checkpoint 1: trace the citation. every NPASS/COCONUT entry can be traced back to a paper. you go read that paper. does it describe someone actually isolating this compound from a living organism? or does it describe someone synthesizing it in a lab and testing it against a biological target? these are very different things, and the database sometimes treats them as the same.
checkpoint 2: search other databases. you take the compound’s structure and look it up in PubChem (a massive public chemistry database) and ChEMBL (a database of bioactive molecules, mostly from drug discovery). if it shows up as a pharmaceutical intermediate, a screening library hit, or a known drug fragment, that’s informative. a genuine natural product usually has a history rooted in isolation studies. a synthetic compound has a history rooted in medicinal chemistry campaigns.
checkpoint 3: ask the biosynthesis question. this is the deepest check. you look at the compound’s structure and ask: could biology actually build this? enzymes follow rules. there are well-characterized families of enzymes that build specific types of molecular scaffolds — terpene synthases build terpenes, polyketide synthases build polyketides, nonribosomal peptide synthetases build unusual peptides. if a compound’s skeleton doesn’t fit into any known biosynthetic logic, that’s a strong signal.
checkpoint 4: look for manufacturing fingerprints. some compounds carry telltale signs of their synthetic origin:
protecting groups still attached: these are chemical “caps” that chemists use to shield reactive parts of a molecule during synthesis, then remove at the end. if a protecting group is still on, the compound is likely a synthetic intermediate, not a finished natural product.
impossible functional group combinations: certain groups (like a nitro group next to a hydrazone next to a halogen) don’t arise from any known biological pathway. they’re signatures of pharmaceutical design.
peracetylation: when every hydroxyl group on a molecule has been capped with an acetyl group, it usually means someone was doing protective chemistry in a flask, not isolating a product from a plant.
iii. four imposters
out of 34 compounds I investigated closely (a representative sample from 325 initially flagged), four turned out to be synthetic:
the chloro-nitro-hydrazone. three red flags in a single molecule. chlorine atoms are rare in natural products. nitro groups are rare in natural products. hydrazone linkages are rare in natural products. all three together? that’s not an accent anymore, that’s a completely different language. the citation traced back to a medicinal chemistry paper, not an isolation study.
the cefdinir intermediate. cefdinir is a pharmaceutical antibiotic: a cephalosporin. the compound in NPASS/COCONUT was a partially-built version of it, an intermediate from the manufacturing process. it ended up in the database because someone studied its biological activity, and the database ingested the structure without distinguishing “was isolated from nature” from “was tested against a biological target.”
the peracetylated soyasaponin. soyasaponins are genuine natural products — they’re found in soybeans. but the version in the database had every hydroxyl group capped with acetyl groups. that’s not how the molecule exists in nature; that’s how it exists in a chemist’s flask after protective derivatization. the database recorded the modified version as if it were the natural one.
the sulfur heterocycle. a compact ring system built around sulfur, with structural features characteristic of synthetic pharmaceutical scaffolds rather than biological assembly. no known natural biosynthetic pathway produces this particular ring system.
iv. why it matters
who cares if a few synthetic compounds sneak into a natural products database?
the answer is that databases are the foundation of computational biology. when researchers train machine learning models to predict “what makes a natural product bioactive,” they’re learning from whatever the database contains. if the database contains synthetic pharmaceutical compounds labeled as natural products, the model learns the wrong patterns. it starts thinking that chloro-nitro-hydrazones are what nature builds, and its predictions drift accordingly.
the same problem cascades into virtual screening, drug discovery pipelines, and ADMET (absorption, distribution, metabolism, excretion, toxicity) prediction. every downstream analysis inherits the assumptions of the data it was built on.
They say the #Greeks carved their fears into silver long before they carved their history into stone. On these ancient coins—small worlds of metal passed from hand to trembling hand—lived creatures that were never meant to breathe in daylight. Look at The horned figure, half-man and half-beast, was not merely a symbol but a warning: a guardian of wild, unknowable forces. Those who crossed him were said to vanish into forests where even the gods dared not walk.
Beside him coils the sea-serpent, part horse, part #dragon , born from the deepest trenches of the world’s first oceans. #Sailors swore they felt its shadow glide beneath their ships, as if the creature on the coin was only a reflection of something still alive below.
See Another serpent, its body twisting in an impossible pattern, represented the chaos that ruled before the creation of order—an echo of the time when monsters, not men, shaped the earth.
And then there is the woman with the serpent’s body, a guardian of #forbidden knowledge. Her beauty was said to draw men close… but the truth in her eyes turned their courage to dust. She did not punish—she simply revealed what their souls truly were.
Hi, I would like to know how to make a list of all the ships in a fandom on AO3. For example, I use the Tag Search on "Transformers - A Media Types", but it shows that Jetfire/Starscream is the most popular with 641, but it is actually only the 6th with 1074. Furthermore, it quickly drops to showing Relationship with a single digit when I know that there are dozens of Relationship with hundreds of Works! Why don't most Works appear? Do you know of a way to find All the ships of a fandom on AO3?
Hey! Sorry for the slow reply... I was traveling and then covid knocked me flat for several weeks. :P
So let's talk about AO3 Tag Search. In general, I'm very excited about recent improvements to this feature... There didn't used to be any way to find the top ships (or characters, or freeform/additional tags) across all of AO3. But now you can* by doing a tag search and sorting by uses (descending order):
*In practice, though you won't exactly get a trustworthy list of top tags (and, as you pointed out, in some cases tags may even be missing! we'll get to that later). You will get a list where the numbers are not correct, sometimes to a bizarre degree:
For example, when you click through on the Derek/Stiles tag, you find far fewer works using the tag (note that these are the public works -- if you're logged in, you see a somewhat higher number, but not as high as in the above screenshot):
I will be posting some stats soon that show different numbers (and a different order) for all of the above top ships. But why is there the discrepancy? Here are several guesses about why some works are wrong in Tag Search (and then I'll get to why some ships are missing and what to do about it):
TAG INFLATION #1: The above numbers probably include tags used in AO3 bookmarks, which increases some of the numbers quite a lot. [Evidence: if you search for top freeform tags, you get tags like "To Read" high on the list, and authors don't use those tags.]
TAG INFLATION #2: The above numbers seem to include draft works. [Evidence: I just tested this out by finding a rare tag with only one use... I created a draft of a new work using that same tag, and even though I didn't publish the work, Tag Search now showed 2 uses of the tag.]
TAG DEFLATION: The above numbers do NOT seem to take tag wrangling into account. Some AO3 tags have a lot of synonyms or subtags, but I think only exact uses of the tag get counted in the above list. [Evidence: I found at a tag with only one use according to tag search, but two works when I clicked the tag (Peter Gabriel/Mike Rutherford). I found that one of the works contained a synonym of the main tag ("Mike Rutherford/Peter Gabriel (Imagined)"). That would match with Tag Search only listing one of work for "Peter Gabriel/Mike Rutherford." And when I created a new draft work that used the main tag, it increase the count in Tag Search for "Peter Gabriel/Mike Rutherford" -- but when I created a new draft work that used the synonym tag, it did not.]
There may also be other factors affecting the overall Tag Search numbers.
Okay, so I suspect #3, tag deflation due to no tag wrangling, is (helping to?) create the unexpectedly low numbers you are seeing for ships like Jetfire/Starscream. I suspect that many people do not use the full canonical tag "Jetfire | Skyfire/Starscream (Transformers)", and those other uses don't get counted in Tag Search. The only way to address this issue is to click through on a tag returned by Tag Search and find out how many works the tag has once you look at its list of works.
But why aren't some ships showing up at all? That's a different question. Here, I suspect the answer again is related to tag wrangling. Every (?) canonical ship tag has at least one parent tag that is a fandom tag (as well as the relevant character tags). You can see the parent tags for Jetfire/Starscream on its tag page:
Skyfire (Transformers), Starscream (Transformers), The Transformers (Cartoon Generation One), The Transformers (IDW Generation One), Transformers (Bay Movies), Transformers (Dreamwave Generation One), Transformers (IDW 2019), Transformers (Marvel Generation One), Transformers - All Media Types, Transformers Animated (2007), Transformers: Armada, Transformers: Beast Wars (Cartoon), Transformers: Cybertron, Transformers: Cyberverse, Transformers: Energon, Transformers: Prime, Transformers: Shattered Glass, Transformers: The Headmasters, Transformers: War for Cybertron (Video Games)
Jetfire/Starscream has "Transformers - All Media Types" as a parent tag, and I suspect that is why it shows up in the Tag Search for that fandom. I would guess that some of the bigger Transformer ships do NOT have that broad fandom as a parent tag. Let's check the parent tags of Megatron/Optimus Prime:
Megatron (Transformers), Optimus Prime, The Transformers (IDW Generation One), Transformers (Bay Movies), Transformers Animated (2007), Transformers: Armada, Transformers: Robots in Disguise (2001), Transformers: Robots in Disguise (2015)
Megatron/Optimus Prime does NOT have "Transformers - All Media Types" as a parent tag. I suspect that's why it didn't show up in your tag search.
So what can you do? Unfortunately, I think the only way to be sure to find all the Transformers ships is to do a Tag Search within each of the different Transformers subfandoms (and I know there are a lot) and then combine the lists of ships you find for each. And then be sure to visit the tag works page for each resulting tag to get the actual number of works, as discussed above. I also discussed other ways to get the find the top relationships here, but I think they're all either less reliable or more arduous than this method, at least for a big fandom like Transformers.
